Multispectral scanning has become an important practical application of radiometry theory. The technique applies the principle that since various types of matter can be characterized by their spectral signature, i.e., their energy emission curve over a broad range of frequencies, classification of a group of various subjects contained within a scene can be accomplished by remotely scanning the scene with a detector sensitive to emitted energy over a broad range of frequencies and comparing the detector output with the known spectral signatures of various subjects believed to be in the area.
This technique implies that known spectral signatures are available prior to the classification analysis. Spectral signatures are computed from and tested in comparison with training samples of multispectral image data selected on the basis of a priori information of a scanned scene, generally a photograph.
The identification of these training samples has in the past represented a bottleneck in the overall multispectral processing scheme. The specific limitation has been the requirement that the operator first display a set of data containing the training sample, then make individual identifications of the coordinates of each data element, and finally compile all of the coordinate identifications to define the training sample.
An objective of the present invention is to provide a method and apparatus for minimizing operator involvement in the training sample identification process, thus to expedite the overall processing scheme.